Managing the operation of multiple wells in a well field of an aquifer is a difficult task. Competing environmental, equipment, and energy costs factor in to each operation decision for each well. However, it is difficult to predict how the wells will interact with each other, and with wells of other well fields that may draw from the same aquifer. Further, it is difficult to predict how the aquifer itself will respond to variations in well pumping operations at different locations in the well field. It is also difficult to predict how pumps will perform under changing aquifer conditions. To address these difficulties, much reliance has been placed on the knowledge acquired by well operators who have manually operated the pumps of a particular well field over years of changing aquifer conditions. While these approaches may have sufficed in the past, overreliance on human judgment can produce inefficiencies in operation, increased energy and equipment costs, and even damage to the aquifer. The inventors have recognized that data driven approaches to managing aquifer operation are needed to complement the judgment of human well operators.